Reward based on priority can only be achieved by making the result publicly available ⇒ no secrecy about discoveries, results are immediately in public domain Think about the difference from IPR system. Should we think about a system of open innovation with recognition of priority?

In Europe, in many countries salaries are fixed by law. Yet, promotion and hiring are still heavily linked to publication record. Some universities explicitly reward with bonuses the high impact publications.

7 / 28

Introduction

Monetary and non-monetary rewards

Evaluation of scientific quality

Monetary incentives Royalties

Rents from patents. Should universities be allowed/encouraged to patent?!

8 / 28

Introduction

Monetary and non-monetary rewards

Evaluation of scientific quality

Monetary incentives Royalties

Rents from patents. Should universities be allowed/encouraged to patent?! Several difficult empirical questions: Does patenting I

... encourage technology transfer and licensing? (perhaps)

8 / 28

Introduction

Monetary and non-monetary rewards

Evaluation of scientific quality

Monetary incentives Royalties

Rents from patents. Should universities be allowed/encouraged to patent?! Several difficult empirical questions: Does patenting I

... encourage technology transfer and licensing? (perhaps)

I

... help to attract private funding? (perhaps)

8 / 28

Introduction

Monetary and non-monetary rewards

Evaluation of scientific quality

Monetary incentives Royalties

Rents from patents. Should universities be allowed/encouraged to patent?! Several difficult empirical questions: Does patenting I

... encourage technology transfer and licensing? (perhaps)

I

... help to attract private funding? (perhaps)

I

... encourage academic inventors? (perhaps)

8 / 28

Introduction

Monetary and non-monetary rewards

Evaluation of scientific quality

Monetary incentives Royalties

Rents from patents. Should universities be allowed/encouraged to patent?! Several difficult empirical questions: Does patenting I

... encourage technology transfer and licensing? (perhaps)

I

... help to attract private funding? (perhaps)

I

... encourage academic inventors? (perhaps)

I

... crowd out basic research? (no hard evidence)

8 / 28

Introduction

Monetary and non-monetary rewards

Evaluation of scientific quality

Monetary incentives Royalties

Rents from patents. Should universities be allowed/encouraged to patent?! Several difficult empirical questions: Does patenting I

... encourage technology transfer and licensing? (perhaps)

I

... help to attract private funding? (perhaps)

I

... encourage academic inventors? (perhaps)

I

... crowd out basic research? (no hard evidence)

In the US, since 1980 Bayh-Dole act grants universities the right to retain property rights to inventions deriving from federally funded research. Similar policies followed up in many countries

8 / 28

Introduction

Monetary and non-monetary rewards

Evaluation of scientific quality

University patenting Figure 4.3: Universities’ and PROs’ patents are increasing under the PCT PRO and university PCT applications worldwide, absolute numbers (left) and as a percentage of total PCT applications (right), 1980-2010

Note: As noted in footnote 1, the distinction between universities and PROs often depends on the definition in a given country. The same note applies to the figures which follow. Source: WIPO Statistics Database, June 2011.

University patenting (and licensing) has increased over past decades, now around 7% Figure 4.4 reports the growing share of university and Among high-income countries, the US has the largest of all PRO patent applications worldwide applications from middleand high-income coun- number of university and PRO filings under the PCT with tries as a share of total PCT applications for three periods

52,303 and 12,698 filings respectively (see Figures 4.5

starting in 1980.

and 4.6).43 The second largest source of PRO applications is France with 9,068, followed by Japan with 6,850.

Figure 4.4: Universities and PROs

9 / 28

(10 percent), Germany and SouthMonetary Africa (8 and percent each). rewards Introduction non-monetary 2007, and less activity in Israel and Evaluation the UK. of scientific quality

University-firm joint patenting Figure 4.9: The share of joint university-firm patent applications under the PCT is increasing rapidly Joint university-firm PCT applications in absolute numbers (left) and as a percentage share of total university PCT applications (right): 1980-2010 High-income countries

/PUFi6OJWFSTJUZýSNDPPXOFSTIJQwSFGFSTUPUIFTJUVBUJPOXIFSFUIFSFBSFBUMFBTUUXPBQQMJDBOUT POFCFJOHBVOJWFSTJUZBOEBOPUIFSCFJOHBDPNQBOZ Inventors are not considered. The share of university-firm applications in total PCT applications by middle-income countries are not shown due to their high volatility. Since 2001 this share has been in the range between 16.9 percent and 34.5 percent. Source: WIPO Statistics Database, June 2011.

University-firm patenting has increased as well. Today around 18% of patents in high-income countries are the result of collaborative research between firms and 150 universities. 10 / 28

Introduction

Monetary and non-monetary rewards

Evaluation of scientific quality

Monetary incentives Royalties

Royalties for academic inventors: I

14% of faculty in the US reported being an inventor of a patent in previous 5 years (Stephan 2012).

I

U.S. universities licensing revenue – $82 million in 1990, $1,9 billion – in 2007. 76% comes from life sciences. Faculty typically get around 42%. Blockbuster University Patents:

How to evaluate scientific quality? Appropriate attribution of merit is key for ensuring correct incentives in sciences How to achieve meritocracy? Typically, scientists and their research are evaluated by peers via peer review process But this process has its own problems. Various issues arise: I Quality is subjective. Evaluations might be affected by herding. I Preferences for the same subfield I Poor incentives of peers. Favoritism and cronyism I Stereotypes Various solutions are discussed/used: I Single/double blind evaluations (information flow vs. bias?) I Conflict of interest rules (better information vs bias?) I Quotas (do they work?) I Bibliometric qualify indicators (can imperfect indicators create bad dynamic incentives?) I Feedback mechanisms: reputation, competition for funds

Common research interests: “It is merely human nature that we overrate the importance of our own types of research and underrate the importance of the types that appeal to others.” (Schumpeter 1954) Personal relationships between candidates and evaluators lead to subjective evaluations

Two implications: I Difficulty to detect biases: connected candidates may have higher chances of success both when connected evaluators are more informed and when evaluators are biased. I Potential inefficiency of conflict of interest rules

We empirically assess the potential problem using information from national scientific qualifications (required for promotion) in Spain during 2002-2006 Several interesting features: I Large-scale: all academic disciplines and several levels of promotion (associate professor (AP) and full professor (FP)) I Variety of connections, both strong and weak (conflict of interest rules barely implemented) I Committee members are randomly assigned to evaluation committees I External validity: relatively similar to the system in place in France, Italy and several other continental european countries Procedure: 1 The Ministry publishes the call for evaluations 2 In the following 20 days candidates can apply 3 Once the list of eligible candidates is formed, evaluators (7 per committee) are selected by random draw out of the list of eligible evaluators 4 Evaluation takes place 16 / 28

Introduction

Monetary and non-monetary rewards

Evaluation of scientific quality

Data Zinovyeva and Bagues (2015 AEJ:Applied)

Overall 967 national committees in 188 disciplines were held during 2002-2006 I

31,750 applications

I

3,573 successful candidates

Pool of evaluators and outcome of the random draw I

29,942 eligible evaluators

I

6,769 committee members

Information: I

Gender, age, and affiliation

I

Publications

I

Participation in dissertations, either as author, advisor or committee member

Weak ties (34% in FP exams, 7% in AP exams) I the evaluator was a member of candidate’s doctoral committee I the evaluator invited the candidate to sit in the thesis committee of one of her students (or vice versa) I the evaluator and the candidate sat on the same thesis committee

3

Indirect ties (17% in FP exams, 14% in AP exams) I same thesis advisor I common thesis committee member I common co-author

Candidates with strong, weak and indirect ties are on average better published and more successful. 18 / 28

Introduction

Monetary and non-monetary rewards

Evaluation of scientific quality

Do connections matter? Zinovyeva and Bagues (2015 AEJ:Applied)

We estimate the causal effect of connections on success: yie = α + βcie + Die γ + ie where yie indicates whether individual i qualified in exam e, cie is the actual number of connections in the committee, and Die is the indicator vector for the exact number of connections that candidate i expects to have in evaluation committee e. In other words, we exploit the random variation of actual committee composition, cie , around expected committee composition, Die . The key assumption is that the selection of committee members was random. More formally, E[(cie ie |Die ] = 0